摘要: |
In the United States, most emissions modeling is done using the MOBILE suite of programs. One of the inputs required is vehicle kilometers of travel (VKT) for each vehicle class as a function of average speed. This information traditionally has been obtained from macroscopic planning models whereby the average speed on a given length of roadway is the same for all vehicle classes. During the past 10 years, however, there has been a definite shift away from macro-level transportation modeling to a more simulation-based approach. In addition to the advances in modeling techniques, the advent of intelligent transportation systems (ITS) has opened numerous possibilities for capturing detailed transportation-related information. The purpose of this paper is to illustrate the trade-offs involved under different aggregation scenarios for estimating vehicular emissions using data sets produced by microsimulation models and ITS. A 22-km section of Interstate 10 in Houston, Texas, was used as the test bed in this study. The VKT and speed data for this corridor were determined using a calibrated TRANSIMS model. This information was then used with the MOBILE5a emission model to compute emission estimates. The vehicular emissions were determined for a broad range of spatial, temporal, and combined spatial and temporal levels of disaggregation. It was found that emission estimates could vary by as much as 20%, depending on how the VKT and speed data are determined or depending on the type of ITS data-collection technology used. |